Identifying individuals at high risk of developing type 2 diabetes (T2DM) is critical for effective targeted interventions. We propose to test the hypothesis that urinary F2- isoprostanes (F2-IsoPs) are a biomarker for the risk of T2DM. In a pilot study, we found that baseline levels of urinary F2-IsoPs are inversely associated with incident T2DM;after adjustment for age, body mass index, and impaired glucose tolerance (IGT)-status, the odds of T2DM was 0.32 (95% CI, 0.12-0.81). This association was similar in the normal (NGT) and IGT sub-groups: ORs were 0.23 and 0.34, respectively. Our data suggest that individuals with lower F2-IsoP levels prior to diagnosis have a 3-fold increased risk for developing T2DM. We published a hypothesis that explains these results and predicts that urinary F2-IsoPs are also inversely associated with the risks of IGT and weight gain. We propose to expand our pilot study to the entire eligible IRAS cohort (n=900). Our primary specific aim is to test the hypothesis that urinary F2-IsoPs are inversely associated with the risk of T2DM. The secondary specific aims are to assess prospective associations between F2-IsoPs and two outcomes: IGT and weight gain. Urinary levels of F2-IsoPs will be measured by a recently developed, high-throughput UPLC-MS/MS method. The proposed research offers an important opportunity to develop a new non- invasive biomarker, urinary F2-IsoPs, which has the potential to predict the risks of diabetes (beyond the known risk factors) and of weight gain, an outcome for which no biomarker is available. PUBLIC HEALTH RELEVANCE Type 2 diabetes is becoming a global epidemic with devastating consequences. Prevention of this disease is possible through lifestyle and pharmacological interventions. Therefore, there is an intensive effort to identify people at high risk. The proposed research offers an opportunity to develop a new biomarker, urinary levels of F2-IsoPs, which has the potential to predict the risk of diabetes beyond the known risk factors. Importantly, this biomarker is non-invasive and can be used in a clinical setting. We also believe that this biomarker can be used to predict weight gain, a very important characteristic for which no biomarkers are available.